Psychology 243 Notes.docx

Psychology 243 What was discussed in class - Why are we doing research? Because we want to learn about human behaviour in psychology. We learn how to understand people, how they feel, how they behave, and why they do what they do, why do they behave the way they do? What can predict...

Psychology 243 What was discussed in class - Why are we doing research? Because we want to learn about human behaviour in psychology. We learn how to understand people, how they feel, how they behave, and why they do what they do, why do they behave the way they do? What can predict that? - The 3 main types of designs to get your research question: Experimental designs, correlation designs, qualitative and mixed methods. Sometimes combining some of these, if it's the best way to get your research question. - What is applicable to all these, are the 7 BASIC STEPS OF RESEARCH DESIGN. So, if you are going out to do a study, you are going to follow all these steps, to get yourself ready, plan and record. 1. **Find and read background research** - You are going to look at a topic you find interesting, and then start looking at background research that is already available. When looking at these sources, you look at what has been studied about the topic, what has not been studied about it yet, and immerse yourself in the data in front of you. 2. **Develop a research question** - With the data available to you, you are going to develop a research question (the focus of your specific study). Note: Qualitative- research question. Quantitative- your hypothesis. 3. **Design a study to test the question** - What is the best way that I can discover how to find an answer for my hypothesis? - However, the design of a study depends on the research question, and tells you whether you are going to do quantitative as an experimental or correlational study, or qualitative. 4. **Apply for ethical approval** - You make sure that everything is explained nicely and elaboratively. You send them an introduction and abstract. The rationale for why you are doing the study, how you plan to go about it, which then goes to the ethics board to make sure it is relevant and noyone will come to harm (ethical approval is essential). - +(this is also different depending on whether its quantitative or qualitative. Note: Quantitative; is data driven, statistically driven. Whereas, Qualitative, is words. It accounts experiences) **7.Write your study up as a research report**, and submit it for publication. **Qualitative data-** involves words, description, and meanings. Takes experiences, thoughs, and feelings in depth to account. Answes questions like "What is it like?", "How does it feel?", "What does it means?". Uses interviews (dialogues), focus groups, observations, and open-ended questions to collected data. Also consists of questionnaires, online discussions, media reports. Analyzed using thematic analysis, coding, and interpretation to identify patterns and themes. (For receiving much deeper information; rich data, you don't need a very big sample group like with quantitative data does). \*NOTE: With Qualitative data you're gonna have a hypothesis. **Quantitative data-** involves numbers and statistics. Measures things that can be counted (eg. Scores, ratings, frequencies). Answers questions like "How many?", "How often?", or "To what extent?". Uses surveys, questionnaires, tests, and rating scales to collect data. Example: A study measuring the average score on a happiness scale before and after a therapy session. **THE FOUR TYPES OF QUANTITATIVE DATA** 1. Nominal Data (categorical, extensive, discrete, mutually exclusive) - Belonging to a category, without any inherent order or ranking. - For example: classifying if someone is (right-, left-, or mixed-handed). - favourite colours (red, blue, green, etc). - blood types (A, B,AB, O) - no order, only labels 2. Ordinal Data (continuous/ hierachal) - Natural order of ranking. - Clear order to data, but distance between points many vary. Shows relative position, but not exact differences. - For example: coming 1^st^, 2^nd^, 3^rd^ place in a race - satifactional ratings (very dissapionted, somewhat dissatisfied, neutral, somewhat satisfied, very satisfied) - educational attainment (High School, college, Bachelor's, Master's) - order, but no exact differences 3. Interval Data (continuous, equal intervals) - Continuous but measurable - Order to data points, fixed points and negative values. - For example: Negative temperatures (-1, -2, -3'C) - IQ scores (80, 90, 100,110) - Exam scores (70, 80, 90, 100) - Equal intervals, but no true zero point 4. Ratio Data (continuous, absolute zero) - Has a true zero point - Allows ratios, and proportions - For example: Weight in kilograms (0 kg, 10 kg, 20 kg, 30 kg, etc) Height (50cm, 60 cm, 70cm, 80cm) Age (20, 30, 40, 50) - Equal intervals, and a true zero point Very important: When you go through the process of developing a research question, you need to think critically of the research you are finding. You need to look at each article and ask yourself if there any limitations to this study? Can you see something that perhaps wasn't done appropriately like did they not treat the sample properly? Was there too small of a sample? Are you finding inconsistencies in the research? What is very important to remember in psychological research, is that the existence of limitations is inevitable. Nobody is capable of conducting a study where there are no issues. However, if you do read an article where they are not including any limitations, you should refrain from using a lot of the information because they might have manipulated the data to create significant findings, to publish it and to look good in the industry. We are all humans, and diverse so there is no way to not have any limitations, as said if no found issues, the data has been skewed. As a result, there is now a movement called the "Open Science movement", where researchers can replicate the research made by other researchers work, to learn from it and have a chance to better their own research. **Three problematic practices:** +-----------------------------------+-----------------------------------+ | Sample sizes | Research or project has "lower | | | power", which means that the | | | sample size in the research is | | | "too small". For example: In a | | | quantitative study, 30 people are | | | interviewed and the researcher | | | wants to extraporate the | | | information, and generalize it to | | | millions of people, which in this | | | case is impossible to do. | +===================================+===================================+ | HARKing | Developing a hypothesis after the | | | data was analyzed/ research is | | | completed (basing the hypothesis | | | on findings). Comes from | | | **H**ypothesizing **A**fter the | | | **R**esults are **K**nown | +-----------------------------------+-----------------------------------+ | P-hacking | Hacking data to get the P-value | | | that indicated a significant | | | result (it tells us whether A | | | caused B, or A is correlated to | | | B) | | | | | | Analysing data repeatedly in | | | different ways until a | | | significant result is found. | +-----------------------------------+-----------------------------------+ **PLAN A RESEARCH QUESTION AND PICK A RESEARCH DESIGN: Example** +-----------------------+-----------------------+-----------------------+ | What you aim to do in | Example research | Research design | | your study | question | needed | +=======================+=======================+=======================+ | Look for a difference | Is there a difference | Experimental designs | | between groups of | in happiness between | (Section 2) | | partipants or | individuals who | | | conditions | report liking or | (Difference= | | | disliking chocolate | Experimental) | +-----------------------+-----------------------+-----------------------+ | Look for a | Is there a | Correlational designs | | relationship between | correlation between | (Section 3) | | two continuous | the amount of | | | variables | chocolate eaten per | | | | week and intelligence | | +-----------------------+-----------------------+-----------------------+ | Aim to identify | What are the main | Qualitative designs | | categories and themes | difficulties that | (Section 4) | | from text based data? | chocolate addicts | | | | encounter when trying | | | | to give up eating | | | | chocolate | | +-----------------------+-----------------------+-----------------------+ \*NOTE: With the diagram above, "difference between groups of participants or conditions", the word "groups" clarifies that its Categorical/Nominal in Experimental data. For example: "Do participants like chocolate? **Yes vs No**?" The yes vs no, is your two groups. **Variables for experiments** - Independent Variable- the variable that is intentionally manipulated or changed by the researcher. The cause or predictor variable. The variable that has an effect on their dependent variable. \*NOTE: Independent variables in experimental studies are always nominal. - Dependent Variable- the variable that is being measured or observed in response to the independent variable. The effect or outcome variable. The variable that is expected to change or be affected by the independent variable. \*NOTE: Dependent variable in experimental study is always continuous. It is most likely your ratio data or interval data. For example, "the level of happiness score of participants, like an intelligence test, which is their happiness score". Relationships between variables Three scatter plots depict positive correlation, no correlation, and negative correlation, respectively. The scatter plots plot intelligence versus bars of chocolate per week. The horizontal axis ranges from 0 through 15, in increments of 5. The vertical axis ranges from 80 through 150, in increments of 10. In the first scatter plot, a best-fit line starts from 0, 90, slopes upward, and terminates at 140. The approximate data from the plot are as follows. 1, 92. 3, 85. 5, 110. 7, 125. 11, 140. 15, 130. In the second scatter plot, the best-fit line starts at 0, 110 and moves parallel to the horizontal axis, as a straight line. Some dots are scattered above the line while some are below. The third scatter plot shows negative correlation. The best-fit line starts at 0, 131. It moves through several points scattered almost along the best-fit line, and then terminates at 13, 80. All data are approximate. Image 1: As people are scoring higher on intelligence, they are scoring high on the amount of chocolate they are eating. \*NOTE: Where one continuous variable increases and the other one also increases, or the one decreases and the other one decreases, is called a "***positive relationship***". Image 2: Regardless of how much chocolate they are eating, intelligence scores are remaining stable. \*NOTE: "No relationship between two variables, where they do not correlate with one another, is called a "***Non-significant relationship***". Image 3: As the one contiuous variable is rising, the other continuous variable is decreasing. We call it a "***Negative relationship***". NB: In correlation studies, we are not saying that A is causing B. We just say that **they co-vary**. **QUALITATIVE ANALYSIS: Thematic Map (reoccuring) found after interviews**  Image: Shows reoccuring themes found in interview, exploring the confounding variables that might influence the individuals' experiences. **VALIDITY AND RELIABILITY IN RESEARCH** **CONDUCTING ETHICAL RESEARCH**  The slide lists elements that a consent form should contain. Title of the project and statements of confirmation, each of which has a Yes or No response. These four statements of confirmation are as follows: 1. confirmation that the study and its aims have been explained. 2. confirmation that they have been able to ask questions about the study. 3. confirmation that they are aware they can withdraw from the study at any time. 4. confirmation that they agree to participate in the study. Finally, the form should include the participant's name, signature, date.  **PSYCHOLOGICAL REPORTS: STRUCTURE** **APA style for statistics** *statistic* (df) = X.XX, *p* =.XXX \*static- The type of analysis calculated is signified by a letter (e.g., r or F) which is italicised. \*df- Degrees of freedom (df) are shown in brackets. X.XX- The calculated value of the statisic is presented to two decimal places..XXX- The p value is presented to three decimal places and the "p" is italicised. APA style for referencing \*Surname then their initials (not full name) \*Before last author, include an ampersand (not "and") \*Year of publication (in brackets) followed by a full stop \*Article title (use sentence case for title) \*Journal title (italicised and each word capitalised) \*Volume number italicised \*Start and end page numbers followed by a full stop \*Digital object identifier (DOI) presented as doi:xxx **For example**: Schumacher, S. E., Kemps, E., & Tiggemann, M. (2016). Bias modification training can alter approach bias and chocolate consumption. *Appetite*, *96*, 219-224. doi: 10.1016/j.appet.2015.09.014